SNR Improvement by Photon Noise Filtering in Ocean Color Monitor Satellite Images
Author(s) -
Ashok Kumar,
Rajiv Kumaran,
Harsh C Trivedi
Publication year - 2016
Publication title -
international journal of image graphics and signal processing
Language(s) - English
Resource type - Journals
eISSN - 2074-9082
pISSN - 2074-9074
DOI - 10.5815/ijigsp.2016.02.08
Subject(s) - noise reduction , computer science , noise (video) , filter (signal processing) , gaussian noise , median filter , artificial intelligence , reduction (mathematics) , computer vision , satellite , signal to noise ratio (imaging) , fast fourier transform , signal (programming language) , remote sensing , algorithm , image processing , image (mathematics) , mathematics , physics , telecommunications , geology , geometry , astronomy , programming language
In high radiometric resolution electro optical image payloads of remote sensing satellites, photon noise dominates SNR performance. Photon noise is input signal dependent and difficult to filter. This paper proposes a photon noise filtering technique for Ocean Color Monitor (OCM) images. Existing filtering techniques are meant for object detection and handles images with poor SNR. As OCM SNR is on higher side, custom sigma filter based denoising technique is developed. Proposed technique first converts photon noise to signal independent Gaussian noise. For this variance stabilization, Anscombe transform is used. Simulations are carried on various images. Proposed technique provides 2050% reduction in overall as well count-wise RMSE. FFT analysis shows significant reduction in noise. Proposed technique is of low complexity.
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